Name: 2022 Joint Statistical Meetings
Start: 2022-08-06T07:00:00+00:00
End: 2022-08-11
Location: Walter E. Washington Convention Center

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Legend:
CC = Walter E. Washington Convention Center M = Marriott Marquis Washington, DC
* = applied session ! = JSM meeting theme

Activity Details

CE_11C	Sun, 8/7/2022, 8:30 AM - 5:00 PM	CC-145B
Gaussian Process Modeling, Design, and Optimization — Professional Development Continuing Education Course
ASA, Section on Physical and Engineering Sciences
Instructor(s): Robert Gramacy, Virginia Tech
This course details statistical techniques at the interface between geostatistics, machine learning, mathematical modeling via computer simulation, calibration of computer models to data from field experiments, and model-based sequential design and optimization under uncertainty (a.k.a. Bayesian Optimization). The treatment will include some of the historical methodology in the literature, and canonical examples, but will primarily concentrate on modern statistical methods, computation and implementation, as well as modern application/data type and size. The course will return at several junctures to real-word experiments coming from the physical, biological and engineering sciences, such as studying the aeronautical dynamics of a rocket booster re-entering the atmosphere; modeling the drag on satellites in orbit; designing a hydrological remediation scheme for water sources threatened by underground contaminants; studying the formation of supernova via radiative shock hydrodynamics; modeling the evolution a spreading epidemic. The course material will emphasize deriving and implementing methods over proving theoretical properties.

15 !	Sun, 8/7/2022, 2:00 PM - 3:50 PM	CC-102A
Subsampling: Basic Tool That Facilitates the Identification of Statistical Relationships in Big Data — Topic Contributed Papers
Section on Statistical Learning and Data Science, International Indian Statistical Association, Section on Physical and Engineering Sciences
Organizer(s): Rakhi Singh, UNC Greensboro
Chair(s): Rakhi Singh, UNC Greensboro
2:05 PM	Unweighted Estimation Based on Optimal Sample Under Measurement Constraints Jing Wang, University of Connecticut
2:25 PM	Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data HaiYing Wang, Uninversity of Connecticut; Aonan Zhang, ByteDance Inc.; Chong Wang, ByteDance Inc.
2:45 PM	Using Subsampling to Speed up Training in Attention-Based NNs: A Case Study at Doing Statistics at Scale in the Amazon Supply Chain Dean p foster, Amazon; Kenny Shirley, Amazon
3:05 PM	Supervised Compression of Big Data Roshan V Joseph, Georgia Institute of Technology; Simon Mak, Duke University
3:25 PM	Subdata Selection Methods John Stufken, UNC Greensboro
3:45 PM	Floor Discussion

24 * !	Sun, 8/7/2022, 2:00 PM - 3:50 PM	CC-154A
High-Performance Statistical Computing: Current Trends and Future Prospects — Topic Contributed Panel
Section on Statistical Computing, Section on Statistical Learning and Data Science, Section on Physical and Engineering Sciences
Organizer(s): Sameh Abdulah, KAUST
Chair(s): Sameh Abdulah, KAUST
2:05 PM	High-Performance Statistical Computing: Current Trends and Future Prospects
Panelists:	Marc Genton, KAUST Dorit Hammerling, Colorado School of Mines Zhengqing Ouyang, University of Massachusetts, Amherst George Ostrouchov, ORNL Hatem Ltaief, KAUST
3:40 PM	Floor Discussion

58	Sun, 8/7/2022, 4:00 PM - 5:50 PM	CC-143C
Q&P and SPES Student Paper Award — Topic Contributed Papers
Quality and Productivity Section, Section on Physical and Engineering Sciences
Organizer(s): Richard Warr, Brigham Young University
Chair(s): Adah Zhang, Sandia National Laboratories
4:05 PM	How to See Hidden Patterns in Metamaterials with Interpretable Machine Learning Zhi Chen, Duke University; Alexander Ogren, Caltech; Chiara Daraio, Caltech; L. Catherine Brinson, Duke University; Cynthia Rudin, Duke University
4:25 PM	Constrained Minimum Energy Designs Chaofan Huang, Georgia Institute of Technology
4:45 PM	Building Degradation Index with Variable Selection for Multivariate Sensory Data Yueyao Wang, Virginia Tech; Ichen Lee, National Cheng Kung University; Yili Hong, Virginia Tech; Xinwei Deng, Virginia Tech
5:05 PM	Vecchia-Approximated Deep Gaussian Processes for Computer Experiments Annie Sauer, Virginia Tech; Andrew Cooper, Virginia Tech; Robert Gramacy, Virginia Tech
5:25 PM	WOOD: Wasserstein-Based Out-of-Distribution Detection Yinan Wang, Virginia Tech; Wenbo Sun, University of Michigan Transportation Research Institute; Judy Jin, University of Michigan; Zhenyu Kong, Virginia Tech; Xiaowei Yue, Virginia Tech
5:45 PM	Floor Discussion

223603	Mon, 8/8/2022, 7:00 AM - 8:30 AM	M-Monument
Section on Physical and Engineering Sciences Business Meeting — Other Cmte/Business
Section on Physical and Engineering Sciences
Chair(s): Lulu Kang, Illinois Institute of Technology

91 * !	Mon, 8/8/2022, 8:30 AM - 10:20 AM	CC-202A
Spatial Statistics and UQ: Foundations for Innovation in Environmental Science — Invited Papers
Section on Statistics and the Environment, Section on Physical and Engineering Sciences, Korean International Statistical Society
Organizer(s): Won Chang, University of Cincinnati
Chair(s): Whitney Huang, Clemson University
8:35 AM	Kernel Flow Emulation for NASA's Surface Biology and Geology Mission Amy Braverman, Jet Propulsion Laboratory, California Institute of Technology; Jouni Susiluoto, Jet Propulsion Laboratory; Houman Owhadi, California Institute of Technology
9:00 AM	Improving Pipelines for Assessing Flood Hazard Under Climate Change Stephan Sain, Jupiter Intelligence
9:25 AM	Hierarchical, Nonstationary, Spatial Modeling to Account for Model Error in Computational Hurricane Models David Higdon, Virginia Tech
9:50 AM	Discussant: Dorit Hammerling, Colorado School of Mines
10:10 AM	Floor Discussion

103	Mon, 8/8/2022, 8:30 AM - 10:20 AM	CC-101
Uncertainty Quantification for Machine Learning — Topic Contributed Papers
Section on Physical and Engineering Sciences, Section on Statistics in Defense and National Security, Uncertainty Quantification in Complex Systems Interest Group
Organizer(s): Michael Grosskopf, Los Alamos National Laboratory; Natalie Klein, Los Alamos National Laboratory
Chair(s): Natalie Klein, Los Alamos National Laboratory
8:35 AM	Myths and Reality in Bayesian Deep Learning Andrew Gordon Wilson, New York University
8:55 AM	Data-Driven Model-Form Uncertainty with Bayesian Statistics and Neural Differential Equations Erin Acquesta, Sandia National Laboratories; Teresa Portone, Sandia National Laboratories; Christopher Rackauckas, Massachusetts Institue of Technology; Raj Dandekar, Massachusetts Institute of Technology
9:15 AM	Generative Modeling Methods in Uncertainty Quantification and Bayesian Inference Youssef Marzouk, Massachusetts Institute of Technology
9:35 AM	Conformal Prediction and Calibration Under Distribution Drift Aaditya Ramdas, Carnegie Mellon University; Aleksandr Podkopaev, Carnegie Mellon University
9:55 AM	Learning Pushforwards for Domain Adaptation Nishant Panda, Los Alamos National Laboratory
10:15 AM	Floor Discussion

104 * !	Mon, 8/8/2022, 8:30 AM - 10:20 AM	CC-144C
Advances in Bayesian Analysis of Computer Models — Topic Contributed Papers
Section on Bayesian Statistical Science, Section on Physical and Engineering Sciences
Organizer(s): Vojtech Kejzlar, Skidmore College
Chair(s): Tapabrata Maiti, Michigan State University
8:35 AM	Bayesian Projected Calibration of Computer Models Fangzheng Xie, Indiana University; Yanxun Xu, Johns Hopkins University
8:55 AM	Using Gradient Descent for Gaussian Process Prediction Matthew Plumlee, Northwestern University
9:15 AM	A Fast and Calibrated Computer Model Emulator: An Empirical Bayes Approach Vojtech Kejzlar, Skidmore College; Mookyong Son, Michigan State University; Shrijita Bhattacharya, Michigan State University; Tapabrata Maiti, Michigan State University
9:35 AM	Double Sequential Calibration Strategy for Stochastic Simulation Models Arindam Fadikar, Argonne National Laboratory
9:55 AM	Theory of Variational Bayes Computer Models Shrijita Bhattacharya, Michigan State University; Mookyong Son, Michigan State University; Vojtech Kejzlar, Skidmore College; Tapabrata Maiti, Michigan State University
10:15 AM	Floor Discussion

107	Mon, 8/8/2022, 8:30 AM - 10:20 PM	CC-140A
SPEED: Statistical Methods, Computing, and Applications Part 1 — Contributed Speed
International Society for Bayesian Analysis (ISBA), Section on Nonparametric Statistics, Section on Physical and Engineering Sciences, Section on Statistical Computing, Section on Statistics in Defense and National Security, Section on Statistics in Genomics and Genetics, WNAR
Chair(s): Rui Xie, University of Central Florida
8:35 AM	The Role of Berkson Paradox in Significance Testing Miodrag Lovric, Radford University
8:40 AM	The growclusters Package for R Randall Powers, Bureau of Labor Statistics; Wendy Martinez, Bureau of Labor Statistics; Terrance D Savitsky, U.S. Bureau of Labor Statistics
8:45 AM	Analysis of Accelerometer Data from NHANES Database Using Fréchet Single Index Model Aritra Ghosal , University of California, Santa Barbara ; Wendy Meiring , University of California Santa Barbara ; Alexander Petersen, Brigham Young University; Marcos Matabuena , University of Santiago de Compostela
8:50 AM	Double Sampling for Informative Coarsening: Considerations for Bias Reduction and Efficiency Gain Alex Levis, Harvard T.H. Chan School of Public Health; Rajarshi Mukherjee, Harvard T.H. Chan School of Public Health; Rui Wang, Harvard T.H. Chan School of Public Health; Sebastien Haneuse, Harvard T.H. Chan School of Public Health
8:55 AM	Double Machine Learning in a Semiparametric Approach: An Innovative Causal Inference for Observational Studies Lynda Aouar, University of Northern Colorado
9:00 AM	A Comparison of Regression Discontinuity Effect Estimation for Small Samples Daryl Swartzentruber, The Ohio State University; Eloise E Kaizar, The Ohio State University
9:05 AM	Reliability for Binary and Ordinal Data in Forensics Hina Arora, University of California Irvine; Naomi Kaplan-Damary, Hebrew University; Hal S. Stern, University of California-Irvine
9:10 AM	Approaching Supersaturated Screening as a Pilot Experiment Michael McKibben, NCSU; Jonathan Stallrich, North Carolina State University
9:15 AM	Bayesian Modeling of Spatial Molecular Profiling Data at the Single-Cell Level Jie Yang, The University of Texas at Dallas; Sunyoung Shin, University of Texas at Dallas; Qiwei Li, The University of Texas at Dallas
9:20 AM	W-BETEL: Bayesian Exponentially Tilted Empirical Likelihood with Parametric Restriction via a Modified Wasserstein Metric Abhisek Chakraborty, Texas A & M University; Anirban Bhattacharya, Texas A&M University; Debdeep Pati, Texas A&M University
9:30 AM	Interpretable Modeling of Genotype-Phenotype Landscapes with State-of-the-Art Predictive Power Peter Tonner, National Institute of Standards and Technology; David Ross, National Institute of Standards and Technology; Abe Pressman, National Institute of Standards and Technology
9:35 AM	Cybersecurity and Infrastructure Security Agency Enterprise Conceptual Data Model Swami Natarajan, The MITRE Corporation
9:40 AM	MCMC-CE: A Novel Approach for Accurate Estimation of the Distributions of Large Quadratic Forms of Normal Variables Bich Na Choi, Medical College of Georgia, Augusta University; Yang Shi, Augusta University
9:50 AM	Bayesian Iterative Conditional Stochastic Search (BICOSS) for GWAS Jacob Williams, Virginia Polytechnic Institute and State University; Marco Ferreira, Virginia Tech
9:55 AM	A Statistical Framework for Deepfake Detection Shannon Gallagher, Software Engineering Institute, Carnegie Mellon University; Catherine Bernaciak, Software Engineering Institute, Carnegie Mellon University; Jeffrey Mellon, Software Engineering Institute, Carnegie Mellon University; Dominic Ross, Software Engineering Institute, Carnegie Mellon University
10:00 AM	Developing Logistic Regression for the High-Dimensional DNA Methylation Data Mohamed salem Milad, Arkansas State University
10:05 AM	A Survey of Likelihood Ratio Method Development and Implementation AcrossMultiple Forensic Disciplines Lulu Chen, University of Central Florida; Larry Tang, University of Central Florida; Jonathon Phillips, National Institute of Standards and Technology
10:10 AM	Modeling Sparse Data Using MLE with Applications to Microbiome Data Hani Aldirawi, California State University San Bernardino

10:15 AM	Floor Discussion

134 * !	Mon, 8/8/2022, 10:30 AM - 12:20 PM	CC-143A
Statistics for Strengthening Inferences from Forensic Evidence — Topic Contributed Papers
Advisory Committee on Forensic Science, Section on Physical and Engineering Sciences, Social Statistics Section
Organizer(s): Karen Kafadar, University of Virginia
Chair(s): Jan Hannig, University of Noerth Carolina at Chapel Hill
10:35 AM	Characterizing Variability in Forensic Decision-Making with Item Response Theory Amanda Luby, Swarthmore College
10:55 AM	An Algorithm for Forensic Toolmark Comparisons Maria Cuellar, University of Pennsylvania; Heike Hofmann, Iowa State University
11:15 AM	NIST Footwear Impression Comparison System (FICS) Steven Lund, National Institute of Standards and Technology; Adam Pintar, National Institute of Standards and Technology
11:35 AM	Discussant: Hari Iyer, National Institute of Standards & Technology
11:55 AM	Discussant: Hal S. Stern, University of California-Irvine
12:15 PM	Floor Discussion

148	Mon, 8/8/2022, 10:30 AM - 12:20 PM	CC-142
Design and Analysis of Experiments — Contributed Papers
Section on Physical and Engineering Sciences
Chair(s): Maria Weese, Miami University
10:35 AM	Optimal Designs for Factor Screening Under the Lasso Herschel Kade Young, North Carolina State University; Jonathan Stallrich, North Carolina State University; Maria Weese, Miami University; Byran J Smucker, Miami University; David J. Edwards, Virginia Commonwealth University
10:50 AM	Inference for the Best Sequence in Order-of-Addition Robert Mee, University of Tennessee; Huo Li, Nankai University
11:05 AM	Optimal Condition-Based Maintenance Policy Under Tweedie Exponential Dispersion Process David Han, UTSA
11:20 AM	Degradation Analysis with Longitudinal Functional Data Quyen N Do, Virginia Tech; Pang Du, Virginia Tech; Yili Hong, Virginia Tech
11:35 AM	Active Learning for the Construction of Digital Twins from Design of Experiment’s Data Rosa Arboretti, University of Padova; Elena Barzizza, Università degli Studi di Padova; Nicolò Biasetton, University of Padova; Riccardo Ceccato, University of Padova; Marta Disegna, University of Padova; Luca Pegoraro, University of Padova; Luigi Salmaso, University of Padova
11:50 AM	Comparison of the Inferential Performance Between Ada-SSALT and Simple SSALT Under an Exponential Lifetime Distribution Haifa Ghassan Ismail-Aldayeh, UTSA; David Han, UTSA
12:05 PM	Floor Discussion

158	Mon, 8/8/2022, 10:30 AM - 11:15 AM	CC-Hall D
SPEED: Statistical Methods, Computing, and Applications Part 2 — Contributed Poster Presentations
International Society for Bayesian Analysis (ISBA), Section on Nonparametric Statistics, Section on Physical and Engineering Sciences, Section on Statistical Computing, Section on Statistics in Defense and National Security, Section on Statistics in Genomics and Genetics
Chair(s): Rui Xie, University of Central Florida
01:	The Role of Berkson Paradox in Significance Testing Miodrag Lovric, Radford University
02:	The growclusters Package for R Randall Powers, Bureau of Labor Statistics; Wendy Martinez, Bureau of Labor Statistics; Terrance D Savitsky, U.S. Bureau of Labor Statistics
03:	Analysis of Accelerometer Data from NHANES Database Using Fréchet Single Index Model Aritra Ghosal , University of California, Santa Barbara ; Wendy Meiring , University of California Santa Barbara ; Alexander Petersen, Brigham Young University; Marcos Matabuena , University of Santiago de Compostela
04:	Double Sampling for Informative Coarsening: Considerations for Bias Reduction and Efficiency Gain Alex Levis, Harvard T.H. Chan School of Public Health; Rajarshi Mukherjee, Harvard T.H. Chan School of Public Health; Rui Wang, Harvard T.H. Chan School of Public Health; Sebastien Haneuse, Harvard T.H. Chan School of Public Health
05:	Double Machine Learning in a Semiparametric Approach: An Innovative Causal Inference for Observational Studies Lynda Aouar, University of Northern Colorado
06:	A Comparison of Regression Discontinuity Effect Estimation for Small Samples Daryl Swartzentruber, The Ohio State University; Eloise E Kaizar, The Ohio State University
07:	Reliability for Binary and Ordinal Data in Forensics Hina Arora, University of California Irvine; Naomi Kaplan-Damary, Hebrew University; Hal S. Stern, University of California-Irvine
08:	Approaching Supersaturated Screening as a Pilot Experiment Michael McKibben, NCSU; Jonathan Stallrich, North Carolina State University
09:	Bayesian Modeling of Spatial Molecular Profiling Data at the Single-Cell Level Jie Yang, The University of Texas at Dallas; Sunyoung Shin, University of Texas at Dallas; Qiwei Li, The University of Texas at Dallas
10:	W-BETEL: Bayesian Exponentially Tilted Empirical Likelihood with Parametric Restriction via a Modified Wasserstein Metric Abhisek Chakraborty, Texas A & M University; Anirban Bhattacharya, Texas A&M University; Debdeep Pati, Texas A&M University
11:	Interpretable Modeling of Genotype-Phenotype Landscapes with State-of-the-Art Predictive Power Peter Tonner, National Institute of Standards and Technology; David Ross, National Institute of Standards and Technology; Abe Pressman, National Institute of Standards and Technology
12:	Cybersecurity and Infrastructure Security Agency Enterprise Conceptual Data Model Swami Natarajan, The MITRE Corporation
13:	MCMC-CE: A Novel Approach for Accurate Estimation of the Distributions of Large Quadratic Forms of Normal Variables Bich Na Choi, Medical College of Georgia, Augusta University; Yang Shi, Augusta University
14:	Taking PDE Solutions from Low-Fidelity to High-Fidelity Using Bayesian Dynamic Function on Function Regression Marie Tuft, Sandia National Laboratories; Daniel Ries, Sandia National Labs
15:	Bayesian Iterative Conditional Stochastic Search (BICOSS) for GWAS Jacob Williams, Virginia Polytechnic Institute and State University; Marco Ferreira, Virginia Tech
16:	A Statistical Framework for Deepfake Detection Shannon Gallagher, Software Engineering Institute, Carnegie Mellon University; Catherine Bernaciak, Software Engineering Institute, Carnegie Mellon University; Jeffrey Mellon, Software Engineering Institute, Carnegie Mellon University; Dominic Ross, Software Engineering Institute, Carnegie Mellon University
17:	Multi-Omics Integrative Analysis for Incomplete Data Using Weighted P-Value Adjustment Approaches Wenda Zhang, University of South Carolina
18:	Developing Logistic Regression for the High-Dimensional DNA Methylation Data Mohamed salem Milad, Arkansas State University
19:	A Survey of Likelihood Ratio Method Development and Implementation AcrossMultiple Forensic Disciplines Lulu Chen, University of Central Florida; Larry Tang, University of Central Florida; Jonathon Phillips, National Institute of Standards and Technology
20:	Modeling Sparse Data Using MLE with Applications to Microbiome Data Hani Aldirawi, California State University San Bernardino

182 *	Mon, 8/8/2022, 2:00 PM - 3:50 PM	CC-154B
Innovations on Teaching Design of Experiments: Active Learning, Data Science, and Computer-Generated Designs — Invited Panel
Section on Physical and Engineering Sciences, Quality and Productivity Section, Section on Statistics and Data Science Education, Caucus for Women in Statistics
Organizer(s): Byran J Smucker, Miami University
Chair(s): David J. Edwards, Virginia Commonwealth University
2:05 PM	Innovative Experimental Design Education: Active Learning, Data Science, and Computer-Generated Designs Presentation
Panelists:	Byran J Smucker, Miami University Nathaniel Stevens, University of Waterloo Jacqueline Asscher, Kinneret College on the Sea of Galilee Alan Vasquez, UCLA

185 * !	Mon, 8/8/2022, 2:00 PM - 3:50 PM	CC-144B
Addressing Important Questions in Climate Science Using Advanced Statistical and Machine-Learning Approaches — Topic Contributed Papers
Section on Statistics and the Environment, ASA Advisory Committee on Climate Change Policy, Section on Physical and Engineering Sciences
Organizer(s): Matthias Katzfuss, Texas A&M University
Chair(s): Bo Li, University of Illinois at Urbana-Champaign
2:05 PM	Prediction of Optimal Compression Settings for Spatiotemporal Climate Data Sets: Benchmarking Statistical and Machine Learning Techniques Dorit Hammerling, Colorado School of Mines; Alexander Pinard, Colorado School of Mines; Allison Baker, National Center for Atmospheric Research
2:25 PM	A Method for Detection and Attribution of Regional Precipitation Change Using Granger Causality Mark Risser, Lawrence Berkeley National Laboratory
2:45 PM	Estimating Changes in Compound Heat-Humidity Extremes: A Conditional Quantile Approach Karen Aline McKinnon, UCLA; Andy Poppick, Carleton College
3:05 PM	Multi-Model Ensemble Analysis with Neural Network Gaussian Processes Trevor Austin Harris, Texas A&M University; Bo Li, University of Illinois at Urbana-Champaign; Ryan Sriver, University of Illinois
3:25 PM	Non-Gaussian Climate Model Analysis via Scalable Bayesian Transport Maps Matthias Katzfuss, Texas A&M University; Florian Schaefer, Georgia Tech
3:45 PM	Floor Discussion

213	Tue, 8/9/2022, 7:00 AM - 8:15 AM	CC-Ballroom Level South Prefunction
Section on Physical and Engineering Sciences A.M. Roundtable Discussion (Added Fee) — Roundtables AM Roundtable Discussion
Section on Physical and Engineering Sciences
TL04:	Data Fusion of Physical and/or Novel Data Types Emily Casleton, Los Alamos National Laboratory

221 * !	Tue, 8/9/2022, 8:30 AM - 10:20 AM	CC-150A
Advanced Statistical Methods in Quality, Business, and Industry — Invited Papers
Quality and Productivity Section, Section on Physical and Engineering Sciences, Association for the Advancement of Artificial Intelligence
Organizer(s): Emmanuel Yashchin, IBM Research
Chair(s): Emmanuel Yashchin, IBM Research
8:35 AM	Detection of Transient Changes and Application in Energy Finance Michael Baron, American University; Sergey V Malov, St. Petersburg State University
9:00 AM	Inspection for Defects in Railways Segments Fabrizio Ruggeri, CNR IMATI; Melike Baykal-Gursoy, Rutgers University; Ayca Altay, Rutgers University; Refik Soyer, George Washington University
9:25 AM	Managing Model Risk Through Explainable Machine Learning Vijay Nair, University of Michigan
9:50 AM	Discussant: Wolfgang Schmid, European University Viadrina, Frankfurt (Oder)
10:15 AM	Floor Discussion

229 * !	Tue, 8/9/2022, 8:30 AM - 10:20 AM	CC-143A
Geostatistical Computing on Modern Parallel Architectures — Topic Contributed Papers
Section on Statistical Computing, Section on Statistical Learning and Data Science, Section on Physical and Engineering Sciences
Organizer(s): Sameh Abdulah, KAUST
Chair(s): Zhuo Qu, King Abdullah University of Science and Technology
8:35 AM	Scalable Gaussian-Process Regression and Variable Selection Using Vecchia Approximations Presentation Jian Cao, Texas A&M University; Matthias Katzfuss, Texas A&M University; Marc Genton, KAUST; Joe Guinness, Cornell University
8:55 AM	Parallel Likelihood Function Optimization to Accelerate Air Pollution Prediction on Large-Scale Systems Mary Lai Salvana, KAUST; Sameh Abdulah, KAUST; Hatem Ltaief, KAUST; Ying Sun, KAUST; Marc Genton, KAUST; David Keyes, King Abdullah University of Science and Technology
9:15 AM	A Sandwich Smoother for Spatio-Temporal Functional Data Joshua French, University of Colorado Denver; Piotr Kokoszka, Colorado State University
9:35 AM	Accelerating Geostatistical Modeling with Mixed-Precision and Tile Low-Rank Algorithms on Large-Scale Qinglei Cao, Innovative Computing Laboratory, University of Tennessee; Sameh Abdulah, KAUST; Rabab Alomairy, KAUST; Yu Pei, Innovative Computing Laboratory, University of Tennessee; Pratik Nag, King Abdullah University of Science and Technology; George Bosilca, Innovative Computing Laboratory, University of Tennessee; Jack Dongarra, Innovative Computing Laboratory, University of Tennessee; Marc Genton, KAUST; David Keyes, King Abdullah University of Science and Technology; Hatem Ltaief, KAUST; Ying Sun, KAUST
9:55 AM	Distributed Inference for a Spatial Bayesian Network with Application to Natural Hazard Risk Assessment Christopher Krapu, Oak Ridge National Laboratory; Nolan Hayes, Oak Ridge National Laboratory; Robert Stewart, Oak Ridge National Laboratory; Amy Rose, Oak Ridge National Laboratory; Alexandre Sorokine, Oak Ridge National Laboratory; Kuldeep Kurte, Oak Ridge National Laboratory
10:15 AM	Floor Discussion

260 !	Tue, 8/9/2022, 10:30 AM - 12:20 PM	CC-144C
Science-Integrated Statistical Learning — Invited Papers
Section on Physical and Engineering Sciences, Section on Statistical Learning and Data Science, Section on Bayesian Statistical Science
Organizer(s): Simon Mak, Duke University
Chair(s): Robert Gramacy, Virginia Tech
10:35 AM	Multi-Stage, Multi-Fidelity Gaussian Process Modeling, with Applications to Emulation of Heavy-Ion Collisions Simon Mak, Duke University
11:05 AM	When Epidemic Models Meet Statistics: Understanding the Impact of Weather and Government Interventions on COVID-19 Outbreak Chih-Li Sung, Michigan State University
11:35 AM	APIK: Active Physics-Informed Kriging Model with Partial Differential Equations C. F. Jeff Wu, Georgia Inst of Tech
12:05 PM	Floor Discussion

265 * !	Tue, 8/9/2022, 10:30 AM - 12:20 PM	CC-143C
Stochastic Processes in Medicine and Medical Engineering: Theoretical Foundations and Applications — Topic Contributed Papers
Section on Medical Devices and Diagnostics, IMS, Section on Physical and Engineering Sciences
Organizer(s): Jan Beran, University of Konstanz
Chair(s): Sucharita Ghosh, Swiss Federal Research Institute WSL
10:35 AM	Functional Time Series Modeling of Mechanically Ventilated Breathing Activity Jan Beran, University of Konstanz
10:55 AM	Scalable Gaussian Process Regression for Biomedical Time-Series Data Jan Graßhoff, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering; Philipp Rostalski, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering
11:15 AM	Incorporating Model Mismatch in a Bayesian Uncertainty Quantification Analysis of a Fluid-Dynamics Model of Pulmonary Blood Circulation Presentation Mihaela Paun, University of Glasgow; Mitchel Colebank, University of California; Mette Olufsen, North Carolina State University; Nicholas Hill, University of Glasgow; Dirk Husmeier, University of Glasgow
11:35 AM	Adaptive Frequency Band Analysis for Multivariate Biomedical Time Series Scott Alan Bruce, Texas A&M University; Raanju Sundararajan, Southern Methodist University
11:55 AM	Benefits of Noise in Biomedical Research: A Multiscale Point of View Brani Vidakovic, Texas A&M University
12:15 PM	Floor Discussion

316 *	Tue, 8/9/2022, 2:00 PM - 3:50 PM	CC-159AB
Advances in Astrostatistics in the Great White North — Invited Papers
SSC (Statistical Society of Canada), Canadian Statistical Sciences Institute, Section on Physical and Engineering Sciences
Organizer(s): David C Stenning, Simon Fraser University
Chair(s): David C Stenning, Simon Fraser University
2:05 PM	Light from the Darkness: Detecting Ultra-Diffuse Galaxies in the Perseus Cluster Using Log-Gaussian Cox Process Dayi (David) Li, University of Toronto
2:30 PM	Mapping the Milky Way in 5-D with Big Data Joshua Shen Speagle, University of Toronto
2:55 PM	Statistical Challenges in Gravitational Wave Astrophysics Mervyn Chan, The University of British Columbia
3:20 PM	Discussant: Derek Bingham, Simon Fraser University
3:45 PM	Floor Discussion

327 * !	Tue, 8/9/2022, 2:00 PM - 3:50 PM	CC-143C
On Surrogate Modeling of Emerging Issues in Physical and Engineering Simulators — Topic Contributed Papers
Section on Physical and Engineering Sciences, ENAR, Section on Bayesian Statistical Science
Organizer(s): Bledar Alex Konomi, University of Cincinnati
Chair(s): Emily L Kang, University of Cincinnati
2:05 PM	A Nonstationary Soft Partitioned Gaussian Process Model via Random Spanning Trees Zhao Tang Luo, Texas A&M University; Huiyan Sang, Texas A&M University; Bani Mallick, Texas A&M University
2:25 PM	Multifidelity Karhunen-Loeve Expansion Surrogate Models for Uncertainty Propagation Xun Huan, University of Michigan; Aniket Jivani, University of Michigan; Cosmin Safta, Sandia National Laboratories
2:45 PM	Dimension Reduction for Gaussian Process Models via Convex Combination of Kernels Lulu Kang, Illinois Institute of Technology
3:05 PM	B-DeepONet: An Enhanced Bayesian DeepONet for Solving Noisy Parametric PDEs Using Accelerated Replica Exchange SGLD Guang Lin, Purdue University; Christian Moya, Purdue University; Zecheng Zhang, Purdue University
3:25 PM	Emulating the Magnitude and Location of the Stormwise Maximum Surge Level Whitney Huang, Clemson University; Taylor Asher, University of North Carolina at Chapel Hill
3:45 PM	Floor Discussion

345	Tue, 8/9/2022, 2:00 PM - 3:50 PM	CC-Hall D
Contributed Poster Presentations: Section on Physical and Engineering Sciences — Contributed Poster Presentations
Section on Physical and Engineering Sciences
Chair(s): Gyuhyeong Goh, Kansas State University
27:	Power BI App to Statistically Assess Bias Between In-Line Inspection Runs for Oil and Gas Pipelines William V Harper, DNV; Adriana Nenciu, Otterbein University; Matt Ellinger, DNV; Eric Graf, DNV; Stacy Hickey, DNV; Tom Bubenik, DNV; Pam Moreno, DNV GL
28:	Conformal Prediction for Model Validation Under Heteroskedasticity and Measurement Errors Naomi Giertych, North Carolina State University; Jonathan P Williams, North Carolina State University
29:	The Pauli Potential in the Metropolis Monte-Carlo Context Guillermo Frank, UIDI-FRBA. Universidad Tecnológica Nacional; Claudio Dorso, IFIBA-CONICET; Jorge López, University of Texas at El Paso
30:	A New Method of Measuring Photonicity in Optically–Dense, Multiphoton–Reactive Systems Peter Hovey, University of Dayton; Mark Masthay, University of Dayton
31:	Linearity Characterization and Uncertainty Quantification for Spectroradiometers Adam Pintar, National Institute of Standards and Technology; Zachary Levine, National Institute of Standards and Technology; Stephen Maxwell, National Institute of Standards and Technology; Howard Yoon, National Institute of Standards and Technology

415 * !	Wed, 8/10/2022, 10:30 AM - 12:20 PM	CC-207B
Astrostatistics: Innovative Statistical Methods for Foundational Astrophysical Sciences — Topic Contributed Papers
Korean International Statistical Society, Section on Physical and Engineering Sciences, Astrostatistics Special Interest Group
Organizer(s): Hyungsuk Tak, Pennsylvania State University
Chair(s): Hyungsuk Tak, Pennsylvania State University
10:35 AM	Using Topological Data Analysis to Distinguish Cosmological Models of Our Universe Jessi Cisewski-Kehe, University of Wisconsin-Madison
10:55 AM	Model Validation and Estimation of Mass-Radius-Flux Distribution for Exoplanets Under Heterogeneous Measurement Errors Presentation Sujit Ghosh, North Carolina State University; Qi Ma, Facebook Inc
11:15 AM	When Geometry and Statistics Meet Cosmology: The Challenge of Detecting Cosmic Webs Presentation Yen-Chi Chen, University of Washington; Yikun Zhang, University of Washington
11:35 AM	Likelihood-Free Frequentist Inference for the Physical Sciences Presentation Luca Masserano, Carnegie Mellon University; Ann Lee, Carnegie Mellon University; Mikael Kuusela, Carnegie Mellon University; Rafael Izbicki, Federal University of São Carlos
11:55 AM	Discussant: Jogesh G. Babu, Pennsylvania State University
12:15 PM	Floor Discussion

416 * !	Wed, 8/10/2022, 10:30 AM - 12:20 PM	CC-102A
Open Problems in Astrostatistics — Topic Contributed Papers
Section on Physical and Engineering Sciences, Astrostatistics Special Interest Group, Section on Bayesian Statistical Science
Organizer(s): Yang Chen, University of Michigan
Chair(s): Yang Chen, University of Michigan
10:35 AM	Calibrated Uncertainty Quantification with Application to Galaxy Photometric Redshifts Ann Lee, Carnegie Mellon University
10:55 AM	Topics for Statistical Advances for Use in Astronomy Herman Marshall, MIT
11:15 AM	Exploring the Quantification of Uncertainty in the Analysis of Multi-Dimensional High-Energy Astronomical Data Sets Aneta Siemiginowska, Center for Astrophysics \| Harvard & Smithsonian
11:35 AM	Discussant: David van Dyk, Imperial College London
11:55 AM	Discussant: Vinay Kashyap, Center for Astrophysics \| Harvard & Smithsonian
12:15 PM	Floor Discussion

448	Wed, 8/10/2022, 12:30 PM - 1:50 PM	CC-Ballroom Level South Prefunction
Section on Physical and Engineering Sciences P.M. Roundtable Discussion (Added Fee) — Roundtables PM Roundtable Discussion
Section on Physical and Engineering Sciences
WL09:	Advances in Design for Computer Experiments Thomas Santner, The Ohio State University

493 * !	Thu, 8/11/2022, 8:30 AM - 10:20 AM	CC-159AB
Uncertainty Quantification for the Mars Sample Return Mission — Invited Papers
Uncertainty Quantification in Complex Systems Interest Group, Section on Physical and Engineering Sciences
Organizer(s): Amy Braverman, Jet Propulsion Laboratory, California Institute of Technology
Chair(s): Maggie Johnson, Jet Propulsion Laboratory, California Institute of Technology
8:35 AM	Uncertainty Quantification for the Mars Sample Return Earth Entry System Landing Kevin Carpenter, Jet Propulsion Laboratory, California Institute of Technology; Aaron Siddens, Jet Propulsion Laboratory, California Institute of Technology; Giuseppe Cataldo, NASA Goddard Space Flight Center; Scott Perino, Jet Propulsion Laboratory, California Institute of Technology,
9:00 AM	Evaluation of Extreme Events and Reliability in the Context of the Mars Sample Return Mission Richard Smith, University of North Carolina Chapel Hill; Dawn Sanderson, University of North Carolina Chapel Hill; Maggie Johnson, Jet Propulsion Laboratory, California Institute of Technology; Amy Braverman, Jet Propulsion Laboratory, California Institute of Technology
9:25 AM	The Containment Assurance Risk Framework of the Mars Sample Return Program Giuseppe Cataldo, NASA Goddard Space Flight Center; Kevin Carpenter, Jet Propulsion Laboratory, California Institute of Technology; Scott Perino, Jet Propulsion Laboratory, California Institute of Technology, ; Aaron Siddens, Jet Propulsion Laboratory, California Institute of Technology
9:50 AM	The Role of Uncertainty Quantification in the Mars Sample Return Mission Ralph Smith, North Carolina State University
10:15 AM	Floor Discussion

512 * !	Thu, 8/11/2022, 8:30 AM - 10:20 AM	CC-204B
Risk Assessment for Autonomous Vehicles — Topic Contributed Papers
Transportation Statistics Interest Group, Section on Physical and Engineering Sciences, Section on Risk Analysis
Organizer(s): David Banks, Duke University
Chair(s): David Banks, Duke University
8:35 AM	Planning a Drive: Autonomous Vehicles and the Role of Statisticians Maria A Terres, Waymo
8:55 AM	Modeling Testable-Case Space for Automated Driving Systems Feng Guo, Virginia Tech
9:15 AM	Data as the Lifeblood of the Transportation System of the Future Robert Heilman, US Dept. of Transportation-Highly Automated Systems Safety Center of Excellence (HASS COE)
9:35 AM	Generative Models for Vehicle Speed Trajectories Vadim Sokolov, George Mason University
9:55 AM	Discussant: Linda Ng Boyle, University of Washington
10:15 AM	Floor Discussion

553 * !	Thu, 8/11/2022, 10:30 AM - 12:20 PM	CC-152A
Future Directions of Climate Statistics — Topic Contributed Panel
Section on Statistics and the Environment, ASA Advisory Committee on Climate Change Policy, Section on Physical and Engineering Sciences
Organizer(s): Whitney Huang, Clemson University
Chair(s): Whitney Huang, Clemson University
10:35 AM	Future Directions of Climate Statistics
Panelists:	Julie Bessac, Argonne National Laboratory Andy Poppick, Carleton College Robert B Lund, University of California - Santa Cruz Ryan Sriver, University of Illinois Alex Cannon, Environment and Climate Change Canada Claudia Tebaldi, Lawrence Berkeley National Laboratory
12:10 PM	Floor Discussion

559 *	Thu, 8/11/2022, 10:30 AM - 12:20 PM	CC-141
Spectral Analysis, Process Monitoring, and Sampling — Contributed Papers
Section on Physical and Engineering Sciences
Chair(s): Arman Sabbaghi, Purdue University
10:35 AM	Adaptive Peak Fitting of Atom Probe Tomography Spectra David Newton, National Institute of Standards and Technology; Frederick Meisenkothen, National Institute of Standards and Technology
10:50 AM	Assessing Similarity of Raman Spectra Hacene Boukari, Delaware State University; Yahira Lopez, Delaware State University; Mohamed Salih, Delaware State University; Fatima Boukari, Delaware State University; Cleon Barnett, Alabama State University; Jobayer Hossain, Nemours Children's Health
11:05 AM	Analysis of Transition Edge Sensor Pulse Height Spectra Kevin J Coakley, National Institute of Standards and Technology
11:20 AM	Scientific Model Building Vs Mathematic Approaches to Statistics: With Applications from Process Monitoring (Often Using Examples with a Headstart, Lucas and Crosier, (1982)) Presentation James M. Lucas, J. M. Lucas and Associates
11:35 AM	Research Synthesis with Missing Uncertainties Andrew Leo Rukhin, National Institute of Standards and technology
11:50 AM	Population Obfuscation: A Masking Problem and Some Solutions Michael Frey, National Institute of Standards and Technology; Adam Wunderlich, National Institute of Standard and Technology; Kyle Caudle, South Dakota School of Mines and Technology; Randy Hoover, South Dakota School of Mines and Technology; Lucas Koepke, National Institute of Standards and Technology; David Newton, National Institute of Standards and Technology
12:05 PM	Floor Discussion

JSM 2022 Conference Program

Activity Details

American Statistical Association